


<!DOCTYPE html>
<!--[if IE 8]><html class="no-js lt-ie9" lang="en" > <![endif]-->
<!--[if gt IE 8]><!--> <html class="no-js" lang="en" > <!--<![endif]-->
<head>
  <meta charset="utf-8">
  <script type="text/javascript">

      var _gaq = _gaq || [];
      _gaq.push(['_setAccount', 'UA-90545585-1']);
      _gaq.push(['_trackPageview']);

      (function() {
        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
      })();
    </script>
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  
  <title>torchvision.datasets.cifar &mdash; Torchvision master documentation</title>
  

  
  
  
  

  

  
  
    

  

  <link rel="stylesheet" href="../../../_static/css/theme.css" type="text/css" />
  <!-- <link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" /> -->
    <link rel="index" title="Index" href="../../../genindex.html" />
    <link rel="search" title="Search" href="../../../search.html" /> 

  
  <script src="../../../_static/js/modernizr.min.js"></script>

  <!-- Preload the theme fonts -->

<link rel="preload" href="../../../_static/fonts/FreightSans/freight-sans-book.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="../../../_static/fonts/FreightSans/freight-sans-medium.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="../../../_static/fonts/IBMPlexMono/IBMPlexMono-Medium.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="../../../_static/fonts/FreightSans/freight-sans-bold.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="../../../_static/fonts/FreightSans/freight-sans-medium-italic.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="../../../_static/fonts/IBMPlexMono/IBMPlexMono-SemiBold.woff2" as="font" type="font/woff2" crossorigin="anonymous">

<!-- Preload the katex fonts -->

<link rel="preload" href="https://cdn.jsdelivr.net/npm/katex@0.10.0/dist/fonts/KaTeX_Math-Italic.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/katex@0.10.0/dist/fonts/KaTeX_Main-Regular.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/katex@0.10.0/dist/fonts/KaTeX_Main-Bold.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/katex@0.10.0/dist/fonts/KaTeX_Size1-Regular.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/katex@0.10.0/dist/fonts/KaTeX_Size4-Regular.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/katex@0.10.0/dist/fonts/KaTeX_Size2-Regular.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/katex@0.10.0/dist/fonts/KaTeX_Size3-Regular.woff2" as="font" type="font/woff2" crossorigin="anonymous">
<link rel="preload" href="https://cdn.jsdelivr.net/npm/katex@0.10.0/dist/fonts/KaTeX_Caligraphic-Regular.woff2" as="font" type="font/woff2" crossorigin="anonymous">
</head>

<div class="container-fluid header-holder tutorials-header" id="header-holder">
  <div class="container">
    <div class="header-container">
      <a class="header-logo" href="https://pytorch.org/" aria-label="PyTorch"></a>

      <div class="main-menu">
        <ul>
          <li>
            <a href="https://pytorch.org/get-started">Get Started</a>
          </li>

          <li>
            <div class="ecosystem-dropdown">
              <a id="dropdownMenuButton" data-toggle="ecosystem-dropdown">
                Ecosystem
              </a>
              <div class="ecosystem-dropdown-menu">
                <a class="nav-dropdown-item" href="https://pytorch.org/hub"">
                  <span class=dropdown-title>Models (Beta)</span>
                  <p>Discover, publish, and reuse pre-trained models</p>
                </a>
                <a class="nav-dropdown-item" href="https://pytorch.org/ecosystem">
                  <span class=dropdown-title>Tools & Libraries</span>
                  <p>Explore the ecosystem of tools and libraries</p>
                </a>
              </div>
            </div>
          </li>

          <li>
            <a href="https://pytorch.org/mobile">Mobile</a>
          </li>

          <li>
            <a href="https://pytorch.org/blog/">Blog</a>
          </li>

          <li>
            <a href="https://pytorch.org/tutorials">Tutorials</a>
          </li>

          <li class="active">
            <a href="https://pytorch.org/docs/stable/index.html">Docs</a>
          </li>

          <li>
            <div class="resources-dropdown">
              <a id="resourcesDropdownButton" data-toggle="resources-dropdown">
                Resources
              </a>
              <div class="resources-dropdown-menu">
                <a class="nav-dropdown-item" href="https://pytorch.org/resources"">
                  <span class=dropdown-title>Developer Resources</span>
                  <p>Find resources and get questions answered</p>
                </a>
                <a class="nav-dropdown-item" href="https://pytorch.org/features">
                  <span class=dropdown-title>About</span>
                  <p>Learn about PyTorch’s features and capabilities</p>
                </a>
              </div>
            </div>
          </li>

          <li>
            <a href="https://github.com/pytorch/pytorch">Github</a>
          </li>
        </ul>
      </div>

      <a class="main-menu-open-button" href="#" data-behavior="open-mobile-menu"></a>
    </div>

  </div>
</div>


<body class="pytorch-body">

   

    

    <div class="table-of-contents-link-wrapper">
      <span>Table of Contents</span>
      <a href="#" class="toggle-table-of-contents" data-behavior="toggle-table-of-contents"></a>
    </div>

    <nav data-toggle="wy-nav-shift" class="pytorch-left-menu" id="pytorch-left-menu">
      <div class="pytorch-side-scroll">
        <div class="pytorch-menu pytorch-menu-vertical" data-spy="affix" role="navigation" aria-label="main navigation">
          <div class="pytorch-left-menu-search">
            

            
              
              
                <div class="version">
                  master (0.6.0 )
                </div>
              
            

            


  


<div role="search">
  <form id="rtd-search-form" class="wy-form" action="../../../search.html" method="get">
    <input type="text" name="q" placeholder="Search Docs" />
    <input type="hidden" name="check_keywords" value="yes" />
    <input type="hidden" name="area" value="default" />
  </form>
</div>

            
          </div>

          
            
            
              
            
            
              <p class="caption"><span class="caption-text">Package Reference</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="../../../datasets.html">torchvision.datasets</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../io.html">torchvision.io</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../models.html">torchvision.models</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../ops.html">torchvision.ops</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../transforms.html">torchvision.transforms</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../utils.html">torchvision.utils</a></li>
</ul>

            
          
        </div>
      </div>
    </nav>

    <div class="pytorch-container">
      <div class="pytorch-page-level-bar" id="pytorch-page-level-bar">
        <div class="pytorch-breadcrumbs-wrapper">
          















<div role="navigation" aria-label="breadcrumbs navigation">

  <ul class="pytorch-breadcrumbs">
    
      <li>
        <a href="../../../index.html">
          
            Docs
          
        </a> &gt;
      </li>

        
          <li><a href="../../index.html">Module code</a> &gt;</li>
        
          <li><a href="../../torchvision.html">torchvision</a> &gt;</li>
        
      <li>torchvision.datasets.cifar</li>
    
    
      <li class="pytorch-breadcrumbs-aside">
        
      </li>
    
  </ul>

  
</div>
        </div>

        <div class="pytorch-shortcuts-wrapper" id="pytorch-shortcuts-wrapper">
          Shortcuts
        </div>
      </div>

      <section data-toggle="wy-nav-shift" id="pytorch-content-wrap" class="pytorch-content-wrap">
        <div class="pytorch-content-left">

        
          
          <div class="rst-content">
          
            <div role="main" class="main-content" itemscope="itemscope" itemtype="http://schema.org/Article">
             <article itemprop="articleBody" id="pytorch-article" class="pytorch-article">
              
  <h1>Source code for torchvision.datasets.cifar</h1><div class="highlight"><pre>
<span></span><span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">os.path</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pickle</span>

<span class="kn">from</span> <span class="nn">.vision</span> <span class="kn">import</span> <span class="n">VisionDataset</span>
<span class="kn">from</span> <span class="nn">.utils</span> <span class="kn">import</span> <span class="n">check_integrity</span><span class="p">,</span> <span class="n">download_and_extract_archive</span>


<div class="viewcode-block" id="CIFAR10"><a class="viewcode-back" href="../../../datasets.html#torchvision.datasets.CIFAR10">[docs]</a><span class="k">class</span> <span class="nc">CIFAR10</span><span class="p">(</span><span class="n">VisionDataset</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;`CIFAR10 &lt;https://www.cs.toronto.edu/~kriz/cifar.html&gt;`_ Dataset.</span>

<span class="sd">    Args:</span>
<span class="sd">        root (string): Root directory of dataset where directory</span>
<span class="sd">            ``cifar-10-batches-py`` exists or will be saved to if download is set to True.</span>
<span class="sd">        train (bool, optional): If True, creates dataset from training set, otherwise</span>
<span class="sd">            creates from test set.</span>
<span class="sd">        transform (callable, optional): A function/transform that takes in an PIL image</span>
<span class="sd">            and returns a transformed version. E.g, ``transforms.RandomCrop``</span>
<span class="sd">        target_transform (callable, optional): A function/transform that takes in the</span>
<span class="sd">            target and transforms it.</span>
<span class="sd">        download (bool, optional): If true, downloads the dataset from the internet and</span>
<span class="sd">            puts it in root directory. If dataset is already downloaded, it is not</span>
<span class="sd">            downloaded again.</span>

<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">base_folder</span> <span class="o">=</span> <span class="s1">&#39;cifar-10-batches-py&#39;</span>
    <span class="n">url</span> <span class="o">=</span> <span class="s2">&quot;https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz&quot;</span>
    <span class="n">filename</span> <span class="o">=</span> <span class="s2">&quot;cifar-10-python.tar.gz&quot;</span>
    <span class="n">tgz_md5</span> <span class="o">=</span> <span class="s1">&#39;c58f30108f718f92721af3b95e74349a&#39;</span>
    <span class="n">train_list</span> <span class="o">=</span> <span class="p">[</span>
        <span class="p">[</span><span class="s1">&#39;data_batch_1&#39;</span><span class="p">,</span> <span class="s1">&#39;c99cafc152244af753f735de768cd75f&#39;</span><span class="p">],</span>
        <span class="p">[</span><span class="s1">&#39;data_batch_2&#39;</span><span class="p">,</span> <span class="s1">&#39;d4bba439e000b95fd0a9bffe97cbabec&#39;</span><span class="p">],</span>
        <span class="p">[</span><span class="s1">&#39;data_batch_3&#39;</span><span class="p">,</span> <span class="s1">&#39;54ebc095f3ab1f0389bbae665268c751&#39;</span><span class="p">],</span>
        <span class="p">[</span><span class="s1">&#39;data_batch_4&#39;</span><span class="p">,</span> <span class="s1">&#39;634d18415352ddfa80567beed471001a&#39;</span><span class="p">],</span>
        <span class="p">[</span><span class="s1">&#39;data_batch_5&#39;</span><span class="p">,</span> <span class="s1">&#39;482c414d41f54cd18b22e5b47cb7c3cb&#39;</span><span class="p">],</span>
    <span class="p">]</span>

    <span class="n">test_list</span> <span class="o">=</span> <span class="p">[</span>
        <span class="p">[</span><span class="s1">&#39;test_batch&#39;</span><span class="p">,</span> <span class="s1">&#39;40351d587109b95175f43aff81a1287e&#39;</span><span class="p">],</span>
    <span class="p">]</span>
    <span class="n">meta</span> <span class="o">=</span> <span class="p">{</span>
        <span class="s1">&#39;filename&#39;</span><span class="p">:</span> <span class="s1">&#39;batches.meta&#39;</span><span class="p">,</span>
        <span class="s1">&#39;key&#39;</span><span class="p">:</span> <span class="s1">&#39;label_names&#39;</span><span class="p">,</span>
        <span class="s1">&#39;md5&#39;</span><span class="p">:</span> <span class="s1">&#39;5ff9c542aee3614f3951f8cda6e48888&#39;</span><span class="p">,</span>
    <span class="p">}</span>

    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">root</span><span class="p">,</span> <span class="n">train</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">target_transform</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
                 <span class="n">download</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>

        <span class="nb">super</span><span class="p">(</span><span class="n">CIFAR10</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">transform</span><span class="p">,</span>
                                      <span class="n">target_transform</span><span class="o">=</span><span class="n">target_transform</span><span class="p">)</span>

        <span class="bp">self</span><span class="o">.</span><span class="n">train</span> <span class="o">=</span> <span class="n">train</span>  <span class="c1"># training set or test set</span>

        <span class="k">if</span> <span class="n">download</span><span class="p">:</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">download</span><span class="p">()</span>

        <span class="k">if</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">_check_integrity</span><span class="p">():</span>
            <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s1">&#39;Dataset not found or corrupted.&#39;</span> <span class="o">+</span>
                               <span class="s1">&#39; You can use download=True to download it&#39;</span><span class="p">)</span>

        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">train</span><span class="p">:</span>
            <span class="n">downloaded_list</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">train_list</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">downloaded_list</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">test_list</span>

        <span class="bp">self</span><span class="o">.</span><span class="n">data</span> <span class="o">=</span> <span class="p">[]</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">targets</span> <span class="o">=</span> <span class="p">[]</span>

        <span class="c1"># now load the picked numpy arrays</span>
        <span class="k">for</span> <span class="n">file_name</span><span class="p">,</span> <span class="n">checksum</span> <span class="ow">in</span> <span class="n">downloaded_list</span><span class="p">:</span>
            <span class="n">file_path</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">root</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">base_folder</span><span class="p">,</span> <span class="n">file_name</span><span class="p">)</span>
            <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">file_path</span><span class="p">,</span> <span class="s1">&#39;rb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
                <span class="n">entry</span> <span class="o">=</span> <span class="n">pickle</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s1">&#39;latin1&#39;</span><span class="p">)</span>
                <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">entry</span><span class="p">[</span><span class="s1">&#39;data&#39;</span><span class="p">])</span>
                <span class="k">if</span> <span class="s1">&#39;labels&#39;</span> <span class="ow">in</span> <span class="n">entry</span><span class="p">:</span>
                    <span class="bp">self</span><span class="o">.</span><span class="n">targets</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">entry</span><span class="p">[</span><span class="s1">&#39;labels&#39;</span><span class="p">])</span>
                <span class="k">else</span><span class="p">:</span>
                    <span class="bp">self</span><span class="o">.</span><span class="n">targets</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">entry</span><span class="p">[</span><span class="s1">&#39;fine_labels&#39;</span><span class="p">])</span>

        <span class="bp">self</span><span class="o">.</span><span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">32</span><span class="p">,</span> <span class="mi">32</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">transpose</span><span class="p">((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span>  <span class="c1"># convert to HWC</span>

        <span class="bp">self</span><span class="o">.</span><span class="n">_load_meta</span><span class="p">()</span>

    <span class="k">def</span> <span class="nf">_load_meta</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="n">path</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">root</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">base_folder</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">meta</span><span class="p">[</span><span class="s1">&#39;filename&#39;</span><span class="p">])</span>
        <span class="k">if</span> <span class="ow">not</span> <span class="n">check_integrity</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">meta</span><span class="p">[</span><span class="s1">&#39;md5&#39;</span><span class="p">]):</span>
            <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s1">&#39;Dataset metadata file not found or corrupted.&#39;</span> <span class="o">+</span>
                               <span class="s1">&#39; You can use download=True to download it&#39;</span><span class="p">)</span>
        <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="s1">&#39;rb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">infile</span><span class="p">:</span>
            <span class="n">data</span> <span class="o">=</span> <span class="n">pickle</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">infile</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s1">&#39;latin1&#39;</span><span class="p">)</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">classes</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">meta</span><span class="p">[</span><span class="s1">&#39;key&#39;</span><span class="p">]]</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">class_to_idx</span> <span class="o">=</span> <span class="p">{</span><span class="n">_class</span><span class="p">:</span> <span class="n">i</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">_class</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">classes</span><span class="p">)}</span>

<div class="viewcode-block" id="CIFAR10.__getitem__"><a class="viewcode-back" href="../../../datasets.html#torchvision.datasets.CIFAR10.__getitem__">[docs]</a>    <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">index</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Args:</span>
<span class="sd">            index (int): Index</span>

<span class="sd">        Returns:</span>
<span class="sd">            tuple: (image, target) where target is index of the target class.</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="n">img</span><span class="p">,</span> <span class="n">target</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">[</span><span class="n">index</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">targets</span><span class="p">[</span><span class="n">index</span><span class="p">]</span>

        <span class="c1"># doing this so that it is consistent with all other datasets</span>
        <span class="c1"># to return a PIL Image</span>
        <span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">fromarray</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>

        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">transform</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
            <span class="n">img</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>

        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">target_transform</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
            <span class="n">target</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">target_transform</span><span class="p">(</span><span class="n">target</span><span class="p">)</span>

        <span class="k">return</span> <span class="n">img</span><span class="p">,</span> <span class="n">target</span></div>

    <span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">)</span>

    <span class="k">def</span> <span class="nf">_check_integrity</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="n">root</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">root</span>
        <span class="k">for</span> <span class="n">fentry</span> <span class="ow">in</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">train_list</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">test_list</span><span class="p">):</span>
            <span class="n">filename</span><span class="p">,</span> <span class="n">md5</span> <span class="o">=</span> <span class="n">fentry</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">fentry</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
            <span class="n">fpath</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">base_folder</span><span class="p">,</span> <span class="n">filename</span><span class="p">)</span>
            <span class="k">if</span> <span class="ow">not</span> <span class="n">check_integrity</span><span class="p">(</span><span class="n">fpath</span><span class="p">,</span> <span class="n">md5</span><span class="p">):</span>
                <span class="k">return</span> <span class="kc">False</span>
        <span class="k">return</span> <span class="kc">True</span>

    <span class="k">def</span> <span class="nf">download</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_check_integrity</span><span class="p">():</span>
            <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Files already downloaded and verified&#39;</span><span class="p">)</span>
            <span class="k">return</span>
        <span class="n">download_and_extract_archive</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">url</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">root</span><span class="p">,</span> <span class="n">filename</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">filename</span><span class="p">,</span> <span class="n">md5</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tgz_md5</span><span class="p">)</span>

    <span class="k">def</span> <span class="nf">extra_repr</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="s2">&quot;Split: </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="s2">&quot;Train&quot;</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">train</span> <span class="ow">is</span> <span class="kc">True</span> <span class="k">else</span> <span class="s2">&quot;Test&quot;</span><span class="p">)</span></div>


<div class="viewcode-block" id="CIFAR100"><a class="viewcode-back" href="../../../datasets.html#torchvision.datasets.CIFAR100">[docs]</a><span class="k">class</span> <span class="nc">CIFAR100</span><span class="p">(</span><span class="n">CIFAR10</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;`CIFAR100 &lt;https://www.cs.toronto.edu/~kriz/cifar.html&gt;`_ Dataset.</span>

<span class="sd">    This is a subclass of the `CIFAR10` Dataset.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">base_folder</span> <span class="o">=</span> <span class="s1">&#39;cifar-100-python&#39;</span>
    <span class="n">url</span> <span class="o">=</span> <span class="s2">&quot;https://www.cs.toronto.edu/~kriz/cifar-100-python.tar.gz&quot;</span>
    <span class="n">filename</span> <span class="o">=</span> <span class="s2">&quot;cifar-100-python.tar.gz&quot;</span>
    <span class="n">tgz_md5</span> <span class="o">=</span> <span class="s1">&#39;eb9058c3a382ffc7106e4002c42a8d85&#39;</span>
    <span class="n">train_list</span> <span class="o">=</span> <span class="p">[</span>
        <span class="p">[</span><span class="s1">&#39;train&#39;</span><span class="p">,</span> <span class="s1">&#39;16019d7e3df5f24257cddd939b257f8d&#39;</span><span class="p">],</span>
    <span class="p">]</span>

    <span class="n">test_list</span> <span class="o">=</span> <span class="p">[</span>
        <span class="p">[</span><span class="s1">&#39;test&#39;</span><span class="p">,</span> <span class="s1">&#39;f0ef6b0ae62326f3e7ffdfab6717acfc&#39;</span><span class="p">],</span>
    <span class="p">]</span>
    <span class="n">meta</span> <span class="o">=</span> <span class="p">{</span>
        <span class="s1">&#39;filename&#39;</span><span class="p">:</span> <span class="s1">&#39;meta&#39;</span><span class="p">,</span>
        <span class="s1">&#39;key&#39;</span><span class="p">:</span> <span class="s1">&#39;fine_label_names&#39;</span><span class="p">,</span>
        <span class="s1">&#39;md5&#39;</span><span class="p">:</span> <span class="s1">&#39;7973b15100ade9c7d40fb424638fde48&#39;</span><span class="p">,</span>
    <span class="p">}</span></div>
</pre></div>

             </article>
             
            </div>
            <footer>
  

  

    <hr>

  

  <div role="contentinfo">
    <p>
        &copy; Copyright 2017, Torch Contributors.

    </p>
  </div>
    
      <div>
        Built with <a href="http://sphinx-doc.org/">Sphinx</a> using a <a href="https://github.com/rtfd/sphinx_rtd_theme">theme</a> provided by <a href="https://readthedocs.org">Read the Docs</a>.
      </div>
     

</footer>

          </div>
        </div>

        <div class="pytorch-content-right" id="pytorch-content-right">
          <div class="pytorch-right-menu" id="pytorch-right-menu">
            <div class="pytorch-side-scroll" id="pytorch-side-scroll-right">
              
            </div>
          </div>
        </div>
      </section>
    </div>

  


  

     
       <script type="text/javascript">
           var DOCUMENTATION_OPTIONS = {
               URL_ROOT:'../../../',
               VERSION:'master',
               LANGUAGE:'None',
               COLLAPSE_INDEX:false,
               FILE_SUFFIX:'.html',
               HAS_SOURCE:  true,
               SOURCELINK_SUFFIX: '.txt'
           };
       </script>
         <script type="text/javascript" src="../../../_static/jquery.js"></script>
         <script type="text/javascript" src="../../../_static/underscore.js"></script>
         <script type="text/javascript" src="../../../_static/doctools.js"></script>
         <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
     

  

  <script type="text/javascript" src="../../../_static/js/vendor/popper.min.js"></script>
  <script type="text/javascript" src="../../../_static/js/vendor/bootstrap.min.js"></script>
  <script src="https://cdnjs.cloudflare.com/ajax/libs/list.js/1.5.0/list.min.js"></script>
  <script type="text/javascript" src="../../../_static/js/theme.js"></script>

  <script type="text/javascript">
      jQuery(function () {
          SphinxRtdTheme.Navigation.enable(true);
      });
  </script> 

  <!-- Begin Footer -->

  <div class="container-fluid docs-tutorials-resources" id="docs-tutorials-resources">
    <div class="container">
      <div class="row">
        <div class="col-md-4 text-center">
          <h2>Docs</h2>
          <p>Access comprehensive developer documentation for PyTorch</p>
          <a class="with-right-arrow" href="https://pytorch.org/docs/stable/index.html">View Docs</a>
        </div>

        <div class="col-md-4 text-center">
          <h2>Tutorials</h2>
          <p>Get in-depth tutorials for beginners and advanced developers</p>
          <a class="with-right-arrow" href="https://pytorch.org/tutorials">View Tutorials</a>
        </div>

        <div class="col-md-4 text-center">
          <h2>Resources</h2>
          <p>Find development resources and get your questions answered</p>
          <a class="with-right-arrow" href="https://pytorch.org/resources">View Resources</a>
        </div>
      </div>
    </div>
  </div>

  <footer class="site-footer">
    <div class="container footer-container">
      <div class="footer-logo-wrapper">
        <a href="https://pytorch.org/" class="footer-logo"></a>
      </div>

      <div class="footer-links-wrapper">
        <div class="footer-links-col">
          <ul>
            <li class="list-title"><a href="https://pytorch.org/">PyTorch</a></li>
            <li><a href="https://pytorch.org/get-started">Get Started</a></li>
            <li><a href="https://pytorch.org/features">Features</a></li>
            <li><a href="https://pytorch.org/ecosystem">Ecosystem</a></li>
            <li><a href="https://pytorch.org/blog/">Blog</a></li>
            <li><a href="https://github.com/pytorch/pytorch/blob/master/CONTRIBUTING.md">Contributing</a></li>
          </ul>
        </div>

        <div class="footer-links-col">
          <ul>
            <li class="list-title"><a href="https://pytorch.org/resources">Resources</a></li>
            <li><a href="https://pytorch.org/tutorials">Tutorials</a></li>
            <li><a href="https://pytorch.org/docs/stable/index.html">Docs</a></li>
            <li><a href="https://discuss.pytorch.org" target="_blank">Discuss</a></li>
            <li><a href="https://github.com/pytorch/pytorch/issues" target="_blank">Github Issues</a></li>
            <li><a href="https://pytorch.org/assets/brand-guidelines/PyTorch-Brand-Guidelines.pdf" target="_blank">Brand Guidelines</a></li>
          </ul>
        </div>

        <div class="footer-links-col follow-us-col">
          <ul>
            <li class="list-title">Stay Connected</li>
            <li>
              <div id="mc_embed_signup">
                <form
                  action="https://twitter.us14.list-manage.com/subscribe/post?u=75419c71fe0a935e53dfa4a3f&id=91d0dccd39"
                  method="post"
                  id="mc-embedded-subscribe-form"
                  name="mc-embedded-subscribe-form"
                  class="email-subscribe-form validate"
                  target="_blank"
                  novalidate>
                  <div id="mc_embed_signup_scroll" class="email-subscribe-form-fields-wrapper">
                    <div class="mc-field-group">
                      <label for="mce-EMAIL" style="display:none;">Email Address</label>
                      <input type="email" value="" name="EMAIL" class="required email" id="mce-EMAIL" placeholder="Email Address">
                    </div>

                    <div id="mce-responses" class="clear">
                      <div class="response" id="mce-error-response" style="display:none"></div>
                      <div class="response" id="mce-success-response" style="display:none"></div>
                    </div>    <!-- real people should not fill this in and expect good things - do not remove this or risk form bot signups-->

                    <div style="position: absolute; left: -5000px;" aria-hidden="true"><input type="text" name="b_75419c71fe0a935e53dfa4a3f_91d0dccd39" tabindex="-1" value=""></div>

                    <div class="clear">
                      <input type="submit" value="" name="subscribe" id="mc-embedded-subscribe" class="button email-subscribe-button">
                    </div>
                  </div>
                </form>
              </div>

            </li>
          </ul>

          <div class="footer-social-icons">
            <a href="https://www.facebook.com/pytorch" target="_blank" class="facebook"></a>
            <a href="https://twitter.com/pytorch" target="_blank" class="twitter"></a>
            <a href="https://www.youtube.com/pytorch" target="_blank" class="youtube"></a>
          </div>
        </div>
      </div>
    </div>
  </footer>

  <div class="cookie-banner-wrapper">
  <div class="container">
    <p class="gdpr-notice">To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: <a href="https://www.facebook.com/policies/cookies/">Cookies Policy</a>.</p>
    <img class="close-button" src="../../../_static/images/pytorch-x.svg">
  </div>
</div>

  <!-- End Footer -->

  <!-- Begin Mobile Menu -->

  <div class="mobile-main-menu">
    <div class="container-fluid">
      <div class="container">
        <div class="mobile-main-menu-header-container">
          <a class="header-logo" href="https://pytorch.org/" aria-label="PyTorch"></a>
          <a class="main-menu-close-button" href="#" data-behavior="close-mobile-menu"></a>
        </div>
      </div>
    </div>

    <div class="mobile-main-menu-links-container">
      <div class="main-menu">
        <ul>
          <li>
            <a href="https://pytorch.org/get-started">Get Started</a>
          </li>

          <li>
            <a href="https://pytorch.org/features">Features</a>
          </li>

          <li>
            <a href="https://pytorch.org/ecosystem">Ecosystem</a>
          </li>

          <li>
            <a href="https://pytorch.org/mobile">Mobile</a>
          </li>

          <li>
            <a href="https://pytorch.org/hub">PyTorch Hub</a>
          </li>

          <li>
            <a href="https://pytorch.org/blog/">Blog</a>
          </li>

          <li>
            <a href="https://pytorch.org/tutorials">Tutorials</a>
          </li>

          <li class="active">
            <a href="https://pytorch.org/docs/stable/index.html">Docs</a>
          </li>

          <li>
            <a href="https://pytorch.org/resources">Resources</a>
          </li>

          <li>
            <a href="https://github.com/pytorch/pytorch">Github</a>
          </li>
        </ul>
      </div>
    </div>
  </div>

  <!-- End Mobile Menu -->

  <script type="text/javascript" src="../../../_static/js/vendor/anchor.min.js"></script>

  <script type="text/javascript">
    $(document).ready(function() {
      mobileMenu.bind();
      mobileTOC.bind();
      pytorchAnchors.bind();
      sideMenus.bind();
      scrollToAnchor.bind();
      highlightNavigation.bind();
      mainMenuDropdown.bind();
      filterTags.bind();

      // Remove any empty p tags that Sphinx adds
      $("[data-tags='null']").remove();

      // Add class to links that have code blocks, since we cannot create links in code blocks
      $("article.pytorch-article a span.pre").each(function(e) {
        $(this).closest("a").addClass("has-code");
      });
    })
  </script>
</body>
</html>